Cardiac Arrhythmia Classification Using Atrial Activity Signal. (2016)

• Record Type: Journal Article
• Authors: Zacharia, Anju Mariyam; Shyjila, P.A.; Kizhakkethottam, Jubilant J.
• Is Part Of: Procedia technology. Volume 24(2016)
• Page Start: 1406
• Page End: 1414
• Publication Date: 2016
• Subjects: Cardiac Arrhythmia -- Atrial electrical activity -- QRS detection.; Technology -- Congresses; Technology -- Periodicals; Engineering -- Congresses; Engineering -- Periodicals; Engineering; Technology; Conference proceedings; Periodicals; 605
• DOI: 10.1016/j.protcy.2016.05.163
• Languages: English
• ISSNs: 2212-0173

Abstract

Abstract: Electrocardiogram (ECG) analysis is the method for cardiac arrhythmia diagnosis. Cardiac arrhythmia is a group of diseases in which the heart beat shows irregularities. The classification of the correct type of Arrhythmia is a necessary and critical issue which becomes difficult in certain cases. In certain cases the Atrial Electrical Activity(AEA) signals are hidden in some other waves and they cannot be detected and classified easily from surface. This paper presents a method by which classification of cardiac arrhythmia is done by processing the ECG. The procedure is done by identifying the QRS complex and thus its position in the preprocessed digitised ECG. The AEA signals in the ECG is identified using a semi-automatic method called Separation Using Maximum Energy Ratio (SUMER), which is found efficient in identifying the hidden waves. In SUMER, an energy ratio based cost function is created and maximized using the gradient ascent method. After identifying the first AEA, the precise positions of all the AEA waves are identified. The ratio between the QRS complex and the AEA waves is calculated and based on the ratio the arrhythmia type is identified. The proposed method would help in better and easy classification of arrhythmia at its early stage.